2 citations · 5 across the 10 of their papers we have counts for
10 papers
Feature extraction for plant growth estimation
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Precision agriculture requires the estimation of plant growth stages in real-time. When the plant growth stage is known, the wastage of resources in cultivation, such as nutrients…
REACH: Interpretability-Driven Feature Identification and Architecture Compression for Multi-Channel Vehicular Channel Estimation
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Multi-channel mixed-SNR training improves out-of-distribution (OOD) generalisation of deep learning channel estimators for IEEE 802.11p vehicular communications, yet the internal m…
Simplified Temporal Convolutional-Based Channel Estimation for a WiFi Vehicular Communication Channel
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie Davel
Channel estimation in vehicular communication is a crucial element in the advancement of intelligent transportation systems. However, the use of pilot signals in the IEEE 802.11p s…
Does simple trump complex? Comparing strategies for adversarial robustness in DNNs
William Brooks, Marelie H. Davel, Coenraad Mouton
Deep Neural Networks (DNNs) have shown substantial success in various applications but remain vulnerable to adversarial attacks. This study aims to identify and isolate the compone…
KnowIt: Deep Time Series Modeling and Interpretation
M. W. Theunissen, R. Rabe, H. L. Potgieter +1
KnowIt (Knowledge discovery in time series data) is a flexible framework for building deep time series models and interpreting them. It is implemented as a Python toolkit, with sou…
Impact of Batch Normalization on Convolutional Network Representations
Hermanus L. Potgieter, Coenraad Mouton, Marelie H. Davel
Batch normalization (BatchNorm) is a popular layer normalization technique used when training deep neural networks. It has been shown to enhance the training speed and accuracy of…
Neural Network-based Vehicular Channel Estimation Performance: Effect of Noise in the Training Set
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
Vehicular communication systems face significant challenges due to high mobility and rapidly changing environments, which affect the channel over which the signals travel. To addre…
A Data Pilot-Aided Temporal Convolutional Network for Channel Estimation in IEEE 802.11p Vehicle-to-Vehicle Communications
Simbarashe Aldrin Ngorima, Albert Helberg, Marelie H. Davel
In modern communication systems, having an accurate channel estimator is crucial. However, when there is mobility, it becomes difficult to estimate the channel and the pilot signal…
Pre-training a Transformer-Based Generative Model Using a Small Sepedi Dataset
Simon P. Ramalepe, Thipe I. Modipa, Marelie H. Davel
Due to the scarcity of data in low-resourced languages, the development of language models for these languages has been very slow. Currently, pre-trained language models have gaine…
Is network fragmentation a useful complexity measure?
Coenraad Mouton, Randle Rabe, Daniël G. Haasbroek +3
It has been observed that the input space of deep neural network classifiers can exhibit `fragmentation', where the model function rapidly changes class as the input space is trave…